AI use-case prioritizer documentation
Rank AI building blocks using explicit reach, impact, confidence, and effort assumptions.
Make the assumptions explicit
The prototype imports a list of AI building blocks and calculates RICE as reach multiplied by impact and confidence, divided by effort. Tier defaults provide a starting point, and scoring assumptions can be adjusted for the evaluation.
Use the results to support a decision
Ranked CSV and JSON exports make the evaluation available for discussion. MoSCoW settings currently apply to the evaluation run as a whole. Use the exported results to discuss any item-specific priorities.
Current availability
The AI use-case prioritizer is a working prototype. Contact NVAA to discuss the opportunities, scoring assumptions, and review process you want to use.